A grid-level residential building stock model (in terms of floor area and replacement value) targeted for seismic risk analysis for mainland China is developed by using census and population density data. Comparison with previous studies and yearbook records indicates the reliability of our model. The model is flexible for updates when more detailed census or statistics data are available, and it can be conveniently combined with hazard data and vulnerability information for risk assessment.
A grid-level residential building stock model (in terms of floor area and replacement value)...
Review status: this discussion paper is a preprint. It has been under review for the journal Natural Hazards and Earth System Sciences (NHESS). The manuscript was not accepted for further review after discussion.
Residential building stock modelling for mainland China
Danhua Xin1,James Edward Daniell1,2,Hing-Ho Tsang3,and Friedemann Wenzel1Danhua Xin et al.Danhua Xin1,James Edward Daniell1,2,Hing-Ho Tsang3,and Friedemann Wenzel1
1Center for Disaster Management and Risk Reduction Technology (CEDIM) and Geophysical Institute, Karlsruhe Institute of Technology, Hertzstrasse 16, 76187, Karlsruhe, Germany
2General Sir John Monash Scholar, The General Sir John Monash Foundation, Level 5, 30 Collins Street, Melbourne, Victoria, 3000, Australia
3Centre for Sustainable Infrastructure, Swinburne University of Technology, Melbourne, VIC 3122, Australia
1Center for Disaster Management and Risk Reduction Technology (CEDIM) and Geophysical Institute, Karlsruhe Institute of Technology, Hertzstrasse 16, 76187, Karlsruhe, Germany
2General Sir John Monash Scholar, The General Sir John Monash Foundation, Level 5, 30 Collins Street, Melbourne, Victoria, 3000, Australia
3Centre for Sustainable Infrastructure, Swinburne University of Technology, Melbourne, VIC 3122, Australia
Received: 16 Nov 2019 – Accepted for review: 05 Jan 2020 – Discussion started: 06 Jan 2020
Abstract. Previous seismic damage reports have shown that the damage and collapse of buildings is the leading cause of fatality and property loss, especially in developing countries. To better serve the risk analysis targeted at near-real-time post-earthquake mitigation and pre-earthquake preparedness and resources allocation, this study develops a fully reproducible grid-level residential building stock model for mainland China, by disaggregating urbanity level census data of each province into 1 km × 1 km scale and using population density profile as the proxy. To evaluate the model performance, the modelled residential building stock value is compared with the net capital stock value in Wu et al. (2014) using perpetual inventory method at provincial level. The modelled stock values in these two studies are in good agreement for all the 31 provinces in mainland China. Furthermore, district level comparison of the residential floor area developed in this study with records from statistical yearbook of Shanghai is also conducted. It turns out that the floor area developed in this study is compatible with floor area recorded in the yearbook of Shanghai. To further validate the applicability of the modelled results in seismic risk assessment, an estimation of the scenario loss to modelled residential buildings is performed, by assuming the recurrence of 2008 Wenchuan M8.0 earthquake. The overall estimated loss approximates the loss value derived from damage reports based on field investigation quite well. Both results indicate the reliability of the residential building stock model developed in this study. The limitations of this study are discussed and directions for future work are recommended.
A grid-level residential building stock model (in terms of floor area and replacement value) targeted for seismic risk analysis for mainland China is developed by using census and population density data. Comparison with previous studies and yearbook records indicates the reliability of our model. The model is flexible for updates when more detailed census or statistics data are available, and it can be conveniently combined with hazard data and vulnerability information for risk assessment.
A grid-level residential building stock model (in terms of floor area and replacement value)...